[Under construction — please excuse the mess]
First, let’s get the naming problem out of the way.
What’s is the difference between big data, analytics, business intelligence, advanced analytics, predictive analytics, enterprise information systems, decision support systems, data science, etc?
The answer is that there are lots of passionate opinions, but no consensus, and so it’s not a useful distinction.
Over the years industry analysts, experts, vendors, and practitioners have created many ever-changing definitions of these terms and how they relate to each other. But there’s so much disagreement that the terms are not practical for effective communication.
The key is that they all have a common goal—to help turn data and information into better business operations. Rather than dig into arcane terminology differences, executives should instead focus on the big picture: the business needs of a particular project, and choosing the technology that fits best.
But isn’t clarity important? Yes, but unfortunately there’s none to be found in these terms. After a while, any term associated with analytics starts sounding dated, and so people in the industry tend to come up with a new one.
Concentrate on the actual problem at hand
Instead of offering yet another definition of the terms above, this book uses the term analytics as a high-level synonym for all of them.
Why? Because business people typically use them all interchangeably to refer to what they need: better access to better data in order to run the business.
Instead of spending time on industry jargon, executives who care about analytics success should focus everybody on two things: the business goals of the project; and the specific technology to be used.
The business goals for analytics tend to be timeless: greater efficiencies, new opportunities, greater profits and market share. Business people have always wanted to be able to understand what has happened in the past, what is happening now, and what will happen in the future..
The technology that’s available, however, is constantly changing and improving. New industry terms are created for these new technologies to help explain why they are different from what came before. And because analytics has been around a long time, this has generated a lot of overlapping terms.
But all these technologies are essentially just different tools, just like spanners, wrenches, and hammers are all useful tools for building a home.
The problem is that many people confuse the technologies available with the business problems to be solved, and end up trying to make home improvements by talking about “hammer problems” or “spanner problems”.
This is a recipe for trouble, because it naturally leads to a focus on the tools rather than the business issue at hand.
Executive leaders have to clearly separate the business goals of any project from the technologies that may be needed to meet those goals.